Centaurea corymbosa is an endemic plant species of La Clape, an region in Southern France.

It is closely related to other Centaurea species found in the region, but unlike C. corymbosa, these are very abundant.

C. corymbosa

Is Centaurea corymbosa threatened because it is not as competitive as other Centaurea species?

• Seeds of two Centaurea species were collected from four populations, two with only C. corymbosa present and two with only C. maculosa present.
• Seeds were sown one per pot.
• Competition was induced by growing Brachypodium ramosum in the pots, but at different densities:
  • Control: no B. ramosum
  • Not dense: B. ramosum covers 10% of the surface area of the pot
  • Dense: B. ramosum covers between 10 and 50% of the surface area of the pot
  • Very dense: B. ramosum covers more than 50% of the surface area of the pot

For each treatment, 50 replicates were seeded for each population and each species, for a total of 800 seeds monitored at different time intervals: each week for 3 weeks, and then once per month*.

• Plante: number of the seed/plant (1 to 800)
• Espece: species (mac, C. maculosa, cor, C. corymbosa)
• Pop: population names
• Traitement: treatment factor
• PAR: quantity of light received by a pot, which depends on the percentage of soil covers ; it is 100% in control pots
• Reference: quantity of light received by a pot where it is not covered. it is 100% in control pots

• Date_de_germination: germination date; missing data if the seed did not germinate
• Cotyledons: size of the emerged seedling
• Taille_Dec_05: size of the rosette in December 2005
• Taille_Fev_06: size of the rosette in Feburary 2006
• Taille_Mars_06: size of the rosette in March 2006
• Taille_Juin_06: size of the rosette in June 2006
• Taille_Sept_06: size of the rosette in September 2006

# Format the date of germination correctly
data$Date_de_germination <- as.Date(data$Date_de_germination,
                                    format = "%d/%m/%Y")

head(data[1:3,1:5])

## # A tibble: 3 x 5
##   Plante Date_de_germination Cotyledons Taille_Dec_05 Taille_Fev_06
##    <dbl> <date>                   <dbl>         <dbl>         <dbl>
## 1      1 NA                          NA             0             0
## 2      2 NA                          NA             0             0
## 3      3 NA                          NA             0             0

1st decision - We are not interested in the rosette size of plants that do not germinate, so set to NA

# If plant didn't germinate, it should not have a rosette size
data_nogerm <- data %>%
  filter(is.na(Date_de_germination)) %>%
  mutate(Taille_Dec_05 = NA,
         Taille_Fev_06 = NA,
         Taille_Mars_06 = NA,
         Taille_Juin_06 = NA,
         Taille_Sept_06 = NA)

data_germ <- data %>%
  filter(!is.na(Date_de_germination))

fulldata <- full_join(data_nogerm, data_germ)

## Joining, by = c("Plante", "Date_de_germination", "Cotyledons", "Taille_Dec_05", "Taille_Fev_06", "Taille_Mars_06", "Taille_Juin_06", "Taille_Sept_06", "traitement", "PAR", "reference", "espece", "pop")

2nd decision: We are interested in the size of the rosette over time, as this will be our indication of how well each plant is coping with the competition.

gathered_data <- fulldata %>%
  rename("2005-12-01" = "Taille_Dec_05",
         "2006-02-01" = "Taille_Fev_06",
         "2006-03-01" = "Taille_Mars_06",
         "2006-06-01" = "Taille_Juin_06",
         "2006-09-01" = "Taille_Sept_06") %>%
  gather(key = "Date", 
         value = "Rosette_size", 
         "2005-12-01":"2006-09-01")

gathered_data$Date <- as.Date(gathered_data$Date, format = "%Y-%m-%d")

3rd decision: To make sense of the light data, we divide the PAR received by the plant through the Brachypodium by the max PAR that pot was receiving (actual/max possible). As the max values were taken for areas within the greenhouse (presumed), not each pot, some values of actual/max are slightly above 1.

gathered_data <- gathered_data %>%
  mutate(light = PAR/reference)

Is light received (actual PAR / Max PAR) perhaps a better measure of competition than the visual sorting of % soil covered?

Something is weird: lack of 0s in the June measurements